Abstract: A method of analyzing unstructured messages is provided.

Abstract: A method associates social media messages with venues. A social network graph includes users, messages from users, and venues. The venues include multiple primary venues and a no-venue. A link between a message and the no-venue node indicates that the message is not associated with a primary venue. Training feature vectors are constructed that measure connectedness between messages and venues. The process trains a classifier to estimate probabilities that messages are associated with venues. A new social media message is received, and the process constructs a feature vector using the same features as the training vectors, measuring connectedness between the new message and the no-venue. The classifier computes a probability that the new message is associated with the no-venue. When the probability exceeds a predefined threshold, the new message is not associated with any of the primary venues. Otherwise, the new message is associated with one of the primary venues.

Abstract: A method of visualizing relationship data in a network connecting an entity of a first type with an entity of a second type is provided. The method includes detecting, within the network, a subnetwork pattern representing at least one relationship satisfying a condition, generating a visualization based on the detected subnetwork pattern. The visualization includes a first region representative of the first type of entity, a second region representative of the second type of entity, and a linking region connecting the first region to the second region and providing information about the at least one relationship satisfying the condition.

Abstract: A method of visualizing search results is provided. The method includes receiving a content feature, detecting, within a network, a subnetwork pattern representing a relationship satisfying a condition and associated with an entity of a first or a second type, the entity being associated with the content feature, and generating a visualization based on the detected subnetwork pattern. The visualization includes a first region representative of the first type of entity, a second region representative of the second type of entity, and a linking region connecting the first region to the second region and providing information about the represented relationship.

Abstract: For tourists, interactions with digital public displays often depend on specific technologies that users may not be familiar with (Quick Response codes, near field communication, and so on) may not have access to because of networking issues, may lack a required application or device technology, may not want to use because of time constraints, or may not want to use because they are worried about sharing their data with a third-party service. Example implementations described herein are directed to a system that allows users to seamlessly share content with a public travel kiosk system.

Abstract: A method and device for displaying a plurality of content items may be shown. The method may include detecting at least one topic associated with each of the plurality of content items, generating a set of topics based on the at least one topic associated with each of the plurality of content items, the set of topics comprising a number of topics associated with the plurality of content items, reducing the number of topics in the set of topics, by combining one of the number of topic in response to a determination that at least one topic in the set of topics is redundant, and generating a visualization, the visualization including at least one content item from the plurality of content items; and the set of topics.

Abstract: A method of visualizing relationship data is illustrated. The method includes receiving relationship data comprising a first type of entities, a second type of entities, and data representative of relationships between an entity of the first type and an entity of the second type, generating, based on the data representative of relationships, a bicluster connecting the entity of the first type to the entity of the second type, and generating a visualization based on the bicluster generated, wherein the visualization includes a first column representative of the first type of entities, and a second column representative of the second type of entities, wherein each row of the visualization corresponds to the generated bicluster.

Abstract: A method and system of targeting information for a user is provided. The method includes collecting one or more digital posts that identify a product and are associated with a digital account, identifying, by a neural network, a stage of a decision model associated with each of the one or more digital posts based on a feature representation generated for each digital post, and transmitting product-related information to the digital account, wherein the transmitting is based on the stage of the decision model identified for each of the one or more digital posts.

Abstract: A method of generating a summary of a media file that comprises a plurality of media segments is provided. The method includes calculating, by a neural network, respective importance scores for each of the media segments, based on content features associated with each of the media segments and a targeting approach, selecting a media segment from the media segments, based on the calculated importance scores, generating a caption for the selected media segment based on the content features associated with the selected media segment, and generating a summary of the media file based on the caption.

Abstract: A method of generating a predictive model of categories of venues visited by a user is provided. The method may include extracting a first content feature from a first digital post to an online social media platform selected from a plurality of digital posts, extracting a second content feature from a second digital post to an online social media platform selected from the plurality of social media posts, aggregating the first and second content features, inferring at least one of a frequency and a regularity of visits to a venue category associated with the plurality of digital posts based on the aggregated first and second content features using a neural network, and determining at least one of a frequently visited venue category and a regularly visited venue category based on the inferred frequency and a regularity of visits associated with the plurality of digital posts.

Abstract: A method and system for generating recommendations. The method including extracting concept information from visual content associated with content posted to a social media platform, detecting one or more preferences based on the extracted concept information, generating a matrix based on the detected one or more preferences, calculating a first similarity between the one or more preferences associated with a first user and one or more preferences associated with a second user based on the generated matrix, and generating a recommendation based on the matrix and the calculated first similarity.

Abstract: The invention described herein is related to antibodies directed to the antigen TIM-1 and uses of such antibodies. In particular, there are provided fully human monoclonal antibodies directed to the antigen TIM-1. Isolated polynucleotide sequences encoding, and amino acid sequences comprising, heavy and light chain immunoglobulin molecules, particularly sequences corresponding to contiguous heavy and light chain sequences spanning the framework regions (FR's) and/or complementarity determining regions (CDR's), specifically from FR1 through FR4 or CDR1 through CDR3, are provided. Hybridomas or other cell lines expressing such immunoglobulin molecules and monoclonal antibodies are also provided.

Abstract: A method of generating a caption for a social media post is provided. The method may include receiving a social media post to be posted to a social media network; collecting reference data relevant to determining common activities occurring at a category of location associated with the social media post; inferring potential topics for captions from a topic inference model, based on the collected reference data associated with the social media post; setting parameters associated with a language model based on the inferred topic; and generating at least one caption for the social media post based on the identified language model, and the inferred topic.

Abstract: Example implementations include a system and method of recognizing behavior of a user. In example implementations, a first post and at least one subsequent post indicative of a product and associated with a first social media account is obtained. A relevance probability is calculated for each of the obtained first post and the at least one subsequent post. The obtained first post and the at least one subsequent post are sequentially analyzed by a second neural network to determine output values relevant to probability of purchasing the product. A probability of purchasing the product is calculated based on the determined output values associated with each post and the calculated relevance probabilities. Product-related information is transmitted to the user associated with the obtained first post based on the determined probability of purchasing the product.

Abstract: A method identifies user demographic characteristics, such as age and gender. First, a plurality of photos are acquired from postings to a social media site by a specific user. A plurality of facial images are identified in the acquired photos. Using a selected subset of the facial images, the method estimates one or more demographic characteristics of the user. In some cases, the estimation uses a profile photograph of the user. In some cases, the facial images are clustered based on similarity. The cluster that most closely matches the profile photo is used for demographic analysis to estimate the characteristics of the user. In some cases, a cluster is selected based on cluster purity, and the images in the cluster are used to estimate the characteristics of the user. In some cases, other self-portrait features are used, such as large facial images or arms along the perimeter of photographs.

Abstract: A method associates social media messages with venues. A social network graph includes users, messages from users, and venues. The venues include multiple primary venues and a no-venue. A link between a message and the no-venue node indicates that the message is not associated with a primary venue. Training feature vectors are constructed that measure connectedness between messages and venues. The process trains a classifier to estimate probabilities that messages are associated with venues. A new social media message is received, and the process constructs a feature vector using the same features as the training vectors, measuring connectedness between the new message and the no-venue. The classifier computes a probability that the new message is associated with the no-venue. When the probability exceeds a predefined threshold, the new message is not associated with any of the primary venues. Otherwise, the new message is associated with one of the primary venues.

Abstract: The invention described herein is related to antibodies directed to the antigen TIM-1 and uses of such antibodies. In particular, there are provided fully human monoclonal antibodies directed to the antigen TIM-1. Isolated polynucleotide sequences encoding, and amino acid sequences comprising, heavy and light chain immunoglobulin molecules, particularly sequences corresponding to contiguous heavy and light chain sequences spanning the framework regions (FR's) and/or complementarity determining regions (CDR's), specifically from FR1 through FR4 or CDR1 through CDR3, are provided. Hybridomas or other cell lines expressing such immunoglobulin molecules and monoclonal antibodies are also provided.

Abstract: A method for inferring venues from social messages includes: accessing a collection of venues and training a classifier that predicts whether a social message is linked to a venue in the collection of venues; receiving a new social message; for each venue in the collection of venues: identifying for the new social message corresponding meta-paths to the particular venue; encoding the corresponding meta-paths as a feature vector for the trained classifier; computing by the trained classifier a score for each venue in the collection of venues indicating whether the new social message is linked to the venue; and based on the scores, identifying at least one candidate venue as a predicted venue for the new social message and associating the predicted venue with the new social message. In some implementations, the new social message is not geotagged.

Abstract: A method includes: obtaining from a first social media source a new short unstructured electronic message with an associated geographic location and message content; identifying a first venue name and a first visit characteristic from the message content; accessing a database of venues, wherein the database includes for respective venues a venue name, a geographic location and one or more venue characteristics, wherein information in the database reflects information associated with the respective venues extracted from a plurality of social media posts, including a plurality of prior short unstructured electronic messages from the first social media source; determining whether the database includes a candidate venue that has a venue name and geographic location that respectively are substantially similar to the first venue name and the associated geographic location; when the candidate venue exists in the database, associating the new short unstructured electronic message with the candidate venue and perform

Abstract: Systems and methods to analyze a person's social media photos or videos, such as those posted on Twitter, Facebook, Instagram, etc. and determine properties of their social life. Using information on the number of people appearing in the photos or videos, their ages, and genders, this method can predict whether the person is in a romantic relationship, has a close family, is a group person, or is single. This information is valuable for generating audiovisual content recommendations as well as for advertisers, because it allows targeting personalized advertisements to the person posting the photos. The described methods may be performed (and the advertisements or other content may be selected for recommendation) substantially in real-time as the user accesses a specific online resource.